Metabolic profiling of biofluids: potential in lung cancer screening and diagnosis

Abstract

The knowledge that the organism’s metabolome is a potentially informative mirror of the impact of disease and its dynamics has led to promising developments in cancer research, strongly geared toward the discovery of new biomarkers of disease onset and progression. The present text reviews the advances made in the last 10 years in lung cancer research making use of the metabolomics strategies, particularly concerning metabolite profiling of human biofluids (blood serum and plasma, urine and others), expected to reflect the deviant metabolic behavior of lung tumors. The main goal of this article is to provide the reader with an up-to-date summary of the main metabolic variations taking place in biofluids, in relation to lung cancer, as well as of the analytical strategies employed to unveil them. Furthermore, particular needs and challenges are identified and possible developments envisaged.

Keywords::

• biofluid
• lung cancer
• metabolomics
• metabonomics
• MS
• NMR
• plasma
• serum
• urine

Financial & competing interests disclosure

Funding is acknowledged from the European Regional Development Fund through the Competitive Factors Thematic Operational Programme and from the Foundation for Science and Technology (FCT), Portugal (PEst-C/CTM/LA0011/2013). CMR acknowledges FCT for the grant SFRH/ BD/63430/2009, and IFD acknowledges Liga Portuguesa Contra o Cancro (LPCC) and CIMAGO (Faculty of Medicine, University of Coimbra). The Portuguese National NMR Network (RNRMN), supported with FCT funds, is also acknowledged. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Key issues

• • Most metabolomics studies on lung cancer have employed MS-based methodologies addressing blood plasma or serum of patients versus controls (mostly healthy subjects).

• • Although less extensively studied, urine and other biofluids have provided complementary information on the metabolic phenotype of lung cancer.

• • There is compelling evidence that lung cancer impacts systemic metabolism and produces detectable metabolic alterations in biofluids, thus setting new possibilities in terms of minimally invasive screening and diagnostic methods.

• • Several studies reported the detection of metabolic alterations at early asymptomatic disease stages, supporting the possible clinical utility of the methodology toward early detection and, therefore, improved prognosis.

• • Although some metabolic alterations are consistent across the literature, others are variable or even discrepant, precluding unique, robust patterns to be established.

• • Present stumbling blocks in lung cancer metabolomics include disease heterogeneity, small subject cohorts, lack of standard operating procedures in sample handling and analysis and need for improved multivariate data analysis and validation methods.

• • Given the heterogeneity of lung tumors, future studies addressing the metabolic profiles of different histological subtypes and disease stages would allow a more comprehensive understanding of lung cancer onset and progression.

• • Information on the specificity of putative lung cancer metabolic markers in relation to other cancer types or other pulmonary pathologies is still lacking, thus calling for collaborative efforts to build this knowledge.